Results from their machine learning-based research to be presented at The Molecular Medicine Tri-Conference in San Francisco.
MOUNTAIN VIEW, Calif.–(BUSINESS WIRE)–February 13, 2018–
Cytobank and the U.S. Food and Drug Administration (FDA) are collaborating to develop machine learning-based methods for characterizing the morphology of multipotent mesenchymal stromal cells (MSCs). These methods could be used in cellular manufacturing processes to characterize cellular preparations with desired immunotherapeutic properties.
The collaboration demonstrates the ability of Cytobank’s cloud-based informatics platform to identify specific subpopulations from a mixed population of MSCs and builds on work done by Steve R. Bauer and colleagues from the FDA and published in PNAS, “The Morphological features of IFN-γ–stimulated mesenchymal stromal cells predict overall immunosuppressive capacity.” This paper discusses how an improved understanding of the morphological features of MSCs will supplement current methods for characterizing these types of cell preparations, which are used in clinical applications involving immunomodulation.
“Machine learning-based approaches like these we are developing with the FDA have been used by our research customers for years to build their understanding of the immune system at the single cell level. We are excited by the potential to apply our proven research approaches in more development related applications, including cell characterization,” said David Craford, President and Chief Executive Officer of Cytobank.
Human MSCs are utilized for multiple clinical applications in regenerative medicine including heart, bone, and neurological conditions. There are approximately 650 clinical trials underway globally. According to Grand View Research the global stem cell market revenue is currently estimated at USD $7B and expected to reach $15B by 2025.
Dr. Katherine Drake, Director of Informatics at Cytobank, will present results from the research in her presentation entitled “Uncovering Hidden Single Cell Biomarkers with Machine Learning” at the Molecular Medicine Tri-Conference Symposium on Single Cell Analysis in San Francisco on February 15, 2018 at 3:00 PM.
About the FDA
The FDA, an agency within the U.S. Department of Health and Human Services, protects the public health by assuring the safety, effectiveness, and security of human and veterinary drugs, vaccines, and other biological products for human use, and medical devices. The agency also is responsible for the safety and security of our nation’s food supply, cosmetics, dietary supplements, products that give off electronic radiation, and for regulating tobacco products.
Cytobank Inc. is the leading cloud-based analysis platform utilizing machine learning algorithms for collaborative biomedical research. Prominent pharmaceutical, biotechnology, and academic researchers around the world use their SaaS solution to develop deep understandings of complex biology at the single cell level. For more information, please visit https://www.cytobank.org/.
Liz Johannesen, 415-613-2497